Sharding
Introduction
By default, Playwright runs test files in parallel and strives for optimal utilization of CPU cores on your machine. In order to achieve even greater parallelisation, you can further scale Playwright test execution by running tests on multiple machines simultaneously. We call this mode of operation "sharding". Sharding in Playwright means splitting your tests into smaller parts called "shards". Each shard is like a separate job that can run independently. The whole purpose is to divide your tests to speed up test runtime.
When you shard your tests, each shard can run on its own, utilizing the available CPU cores. This helps speed up the testing process by doing tasks simultaneously.
In a CI pipeline, each shard can run as a separate job, making use of the hardware resources available in your CI pipeline, like CPU cores, to run tests faster.
Sharding tests between multiple machines
To shard the test suite, pass --shard=x/y
to the command line. For example, to split the suite into four shards, each running one fourth of the tests:
npx playwright test --shard=1/4
npx playwright test --shard=2/4
npx playwright test --shard=3/4
npx playwright test --shard=4/4
Now, if you run these shards in parallel on different jobs, your test suite completes four times faster.
Note that Playwright can only shard tests that can be run in parallel. By default, this means Playwright will shard test files. Learn about other options in the parallelism guide.
Balancing Shards
Sharding can be done at two levels of granularity depending on whether you use the testProject.fullyParallel option or not. This affects how the tests are balanced across the shards.
Sharding with fullyParallel
When fullyParallel: true
is enabled, Playwright Test runs individual tests in parallel across multiple shards, ensuring each shard receives an even distribution of tests. This allows for test-level granularity, meaning each shard will attempt to balance the number of individual tests it runs. This is the preferred mode for ensuring even load distribution when sharding, as Playwright can optimize shard execution based on the total number of tests.
Sharding without fullyParallel
Without the fullyParallel setting, Playwright Test defaults to file-level granularity, meaning entire test files are assigned to shards. In this case, the number of tests per file can greatly influence shard distribution. If your test files are not evenly sized (i.e., some files contain many more tests than others), certain shards may end up running significantly more tests, while others may run fewer or even none.
Key Takeaways:
- With
fullyParallel: true
: Tests are split at the individual test level, leading to more balanced shard execution. - Without
fullyParallel
: Tests are split at the file level, so to balance the shards, it's important to keep your test files small and evenly sized. - To ensure the most effective use of sharding, especially in CI environments, it is recommended to use
fullyParallel: true
when aiming for balanced distribution across shards. Otherwise, you may need to manually organize your test files to avoid imbalances.
Merging reports from multiple shards
In the previous example, each test shard has its own test report. If you want to have a combined report showing all the test results from all the shards, you can merge them.
Start with adding blob
reporter to the config when running on CI:
export default defineConfig({
testDir: './tests',
reporter: process.env.CI ? 'blob' : 'html',
});
Blob report contains information about all the tests that were run and their results as well as all test attachments such as traces and screenshot diffs. Blob reports can be merged and converted to any other Playwright report. By default, blob report will be generated into blob-report
directory.
To merge reports from multiple shards, put the blob report files into a single directory, for example all-blob-reports
. Blob report names contain shard number, so they will not clash.
Afterwards, run npx playwright merge-reports
command:
npx playwright merge-reports --reporter html ./all-blob-reports
This will produce a standard HTML report into playwright-report
directory.
GitHub Actions example
GitHub Actions supports sharding tests between multiple jobs using the jobs.<job_id>.strategy.matrix
option. The matrix
option will run a separate job for every possible combination of the provided options.
The following example shows you how to configure a job to run your tests on four machines in parallel and then merge the reports into a single report. Don't forget to add reporter: process.env.CI ? 'blob' : 'html',
to your playwright.config.ts
file as in the example above.
- First we add a
matrix
option to our job configuration with theshardTotal: [4]
option containing the total number of shards we want to create andshardIndex: [1, 2, 3, 4]
with an array of the shard numbers. - Then we run our Playwright tests with the
--shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }}
option. This will run our test command for each shard. - Finally we upload our blob report to the GitHub Actions Artifacts. This will make the blob report available to other jobs in the workflow.
name: Playwright Tests
on:
push:
branches: [ main, master ]
pull_request:
branches: [ main, master ]
jobs:
playwright-tests:
timeout-minutes: 60
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
shardIndex: [1, 2, 3, 4]
shardTotal: [4]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: lts/*
- name: Install dependencies
run: npm ci
- name: Install Playwright browsers
run: npx playwright install --with-deps
- name: Run Playwright tests
run: npx playwright test --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }}
- name: Upload blob report to GitHub Actions Artifacts
if: ${{ !cancelled() }}
uses: actions/upload-artifact@v4
with:
name: blob-report-${{ matrix.shardIndex }}
path: blob-report
retention-days: 1
- After all shards have completed, you can run a separate job that will merge the reports and produce a combined HTML report. To ensure the execution order, we make the
merge-reports
job depend on our shardedplaywright-tests
job by addingneeds: [playwright-tests]
.
jobs:
...
merge-reports:
# Merge reports after playwright-tests, even if some shards have failed
if: ${{ !cancelled() }}
needs: [playwright-tests]
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: lts/*
- name: Install dependencies
run: npm ci
- name: Download blob reports from GitHub Actions Artifacts
uses: actions/download-artifact@v4
with:
path: all-blob-reports
pattern: blob-report-*
merge-multiple: true
- name: Merge into HTML Report
run: npx playwright merge-reports --reporter html ./all-blob-reports
- name: Upload HTML report
uses: actions/upload-artifact@v4
with:
name: html-report--attempt-${{ github.run_attempt }}
path: playwright-report
retention-days: 14
You can now see the reports have been merged and a combined HTML report is available in the GitHub Actions Artifacts tab.
Merge-reports CLI
npx playwright merge-reports path/to/blob-reports-dir
reads all blob reports from the passed directory and merges them into a single report.
When merging reports from different OS'es you'll have to provide an explicit merge config to disambiguate which directory should be used as tests root.
Supported options:
-
--reporter reporter-to-use
Which report to produce. Can be multiple reporters separated by comma.
Example:
npx playwright merge-reports --reporter=html,github ./blob-reports
-
--config path/to/config/file
Specifies the Playwright configuration file with output reporters. Use this option to pass additional configuration to the output reporter. This configuration file can differ from the one used during the creation of blob reports.
Example:
npx playwright merge-reports --config=merge.config.ts ./blob-reports
merge.config.tsexport default {
testDir: 'e2e',
reporter: [['html', { open: 'never' }]],
};